The difficulty in obtaining a continuous rock elastic properties (REP) profile from triaxial test makes calibration of geomechanical characterization models subjective. The impulse hammer method however provides reliable, reproducible, and continuous proxy for REP dataset, allowing for rock profiling. The relationship between the REP from these two techniques is not well understood, this study employed multivariate data reduction analysis and modeling to extract relevant correlations between Impulse Hammer and Triaxial derived REP. We derived a Young's modulus proxy called reduced Young's modulus (E*) from core plug samples. The E* was acquired from each sample systematically with respect to rock heterogeneity, grain size, and macropore size. The E* was taken as an average of nine impulse hammer runs per sample on equally spaced gridded location on each sample surface. Dynamic Young's modulus (Ed) and static Young's modulus (Es) were derived from the conventional triaxial test. The geochemical analyses were carried out to capture the mineralogical variations in the selected samples. We used statistical analysis and modeling to establish empirical relationship between Impulse Hammer and Triaxial derived RMP.

The results showed that, E* reliably captures the variables within the rock elastic properties. A strong correlation between the Ed, Es, and E* were observed in the samples. We also observed that E*, reveals details of several geomechanical heterogeneity and anisotropy which are not possible with traditional triaxial method. The results show that the empirical relationship between E and E* can be established to generate a continuous REP profile.

Sample availability, representativeness, time, and cost are common challenges in traditional triaxial test. The Impulse Hammer method is a non-destructive technique that significantly saves time, and has a promising cost efficient workflow, which provides reliable, reproducible and continuous rock mechanical properties profile. A robust geomechanical characterization and model calibration can be performed by combining the outputs obtained from these two methods.

Geochemical analysis of rocks is fundamental to the understanding of geology and earth sciences. X-ray dispersive spectrometry and other automated techniques are increasingly being used to determined and quantify the abundances of the major, trace elements and other rock properties. This study utilized a combination of dispersive spectrometric techniques (MicroXRF) and impulse rebound hammer method to establish links between geochemical and mechanical properties of rocks through a non-destructive method. MicroXRF has high resolution and can detect trace elements within the parts per billion range. The micro-rebound hammer was used to generate a reduced Young's modulus (E*), which gives a measure of the rock strength with negligible impact on the rock itself.

In order to explore, visualize and understand the dataset generated, principal component analysis (PCA) was applied to emphasize variation and bring out strong patterns in the dataset. The first two dimensions of PCA express 57.09% of the total dataset inertia; that means that 57.09% total variability in the data is explained by the planes/dimensions. The first dimension, which showed a strong positive correlation to clay forming minerals and rock strength, was tentatively identified as the clay gradient. The second dimension describes diagenetic alteration processes responsible for the enrichment of elements such as Ni, Mo etc. Further, a positive correlation was established between E* and four elements Cobalt (Co), Strontium (Sr), Titanium (Ti), and Zircon (Zr). Remarkably, Silicon (Si) had a negative correlation with all elements but positive correlation with porosity and permeability. We therefore identified Co, Ti, Sr, and Zr as proxy for the determination of rock strength specific for studied samples and proposed a workflow based on our sequences of analysis and interpretation. Furthermore, we identified four chemo- mechanical facies through hierarchical clustering of the product of the PCA.

This presented methodology could be specifically useful for geomechanical characterization of rocks; a key requirement needed for in-situ stresses estimation, wellbore stability analysis, reservoir stimulation and compaction, pore pressure prediction, and more importantly for characterizing drill cuttings where size and time are limiting. Drilling operations require constantly evolving cost effective and time efficient techniques, the proposed workflow will serve these purposes i.e. rapid determination of elemental composition (microxrf) coupled with E*will give a reliable proxy for rock strength. The technique can be applied to, drill cuttings, slabs and whole core directly without prior sample preparation.

Introduction

Geomechanical characterization of subsurface rocks is important for many applications throughout the asset life cycle such as borehole instability, pore pressure prediction, seal breach and fault reactivation, drill bits and drilling parameters selection, sand production, hydraulic fracturing, and reservoir compaction (Meyers et al., 2005; Klimentos, 2005; Germay et al., 2017). A key component of Geomechanical characterization is the model calibration with reliable core data. Typically, core data calibration is performed using triaxial tests data output, such as the uniaxial compressive strength (UCS) and elastic properties of rocks (Young's modulus, Poisson's ratio, etc.), that are empirically linked to wireline data. Sample availability, representativeness, time, and cost are problems associated with core-based rock measurements for mechanical properties [3; 4]. There is also the issue of uncertainty associated with upscaling laboratory generated data with wireline data. Core-based measurement output is usually very limited, hardly constitutes statistically representative data as compare to large data from wireline logs, making it difficult to generate a reliable empirical correlation. Another issue is the inherent heterogeneity in rocks, which varies from nano to field scales. This makes establishment of empirical relationship between scattered core data and wireline data a subjective task. Even rocks that appear identically twin in bulk properties can vary widely in microstructure. Characterizing such reservoir-scale heterogeneities requires statistically representative data and the problems associated with core-based measurement make such substantial number of data points requirement an abominable.

Successful exploitation of shale reservoirs largely depends on the effectiveness of hydraulic fracturing stimulation program. Favorable results have been attributed to intersection and reactivation of pre-existing fractures by hydraulically-induced fractures that connect the wellbore to a larger fracture surface area within the reservoir rock volume. Thus, accurate estimation of the stimulated reservoir volume (SRV) becomes critical for the reservoir performance simulation and production analysis. Micro-seismic events (MS) have been commonly used as a proxy to map out the SRV geometry, which could be erroneous because not all MS events are related to hydraulic fracture propagation. The case studies discussed here utilized a fully 3-D simulation approach to estimate the SRV.

The simulation approach presented in this paper takes into account the real-time changes in the reservoir's geomechanics as a function of fluid pressures. It is consisted of four separate coupled modules: geomechanics, hydrodynamics, a geomechanical joint model for interfacial resolution, and an adaptive re-meshing. Reservoir stress condition, rock mechanical properties, and injected fluid pressure dictate how fracture elements could open or slide. Critical stress intensity factor was used as a fracture criterion governing the generation of new fractures or propagation of existing fractures and their directions. Our simulations were run on a Cray XC-40 HPC system.

The studies outcomes proved the approach of using MS data as a proxy for SRV to be significantly flawed. Many of the observed stimulated natural fractures are stress related and very few that are closer to the injection field are connected. The situation is worsened in a highly laminated shale reservoir as the hydraulic fracture propagation is significantly hampered. High contrast in the in-situ stresses related strike-slip developed thereby shortens the extent of SRV. However, far field nature fractures that were not connected to hydraulic fracture were observed being stimulated.

These results show the beginning of new understanding into the physical mechanisms responsible for greater disparity in stimulation results within the same shale reservoir and hence the SRV. Using the appropriate methodology, stimulation design can be controlled to optimize the responses of in-situ stresses and reservoir rock itself.

The recent crash in the oil market has allowed the industry to reduce the pace of evaluation and completion decisions in unconventional reservoirs, and turn to a more science-based decision-making process for project execution. The traditional stimulation design based on the geometric spacing of induced fractures is now gradually changing to geological spacing (i.e., a design based on an understanding of the reservoir geology) to enhance hydraulic fracture stimulation effectiveness for drastically reduced cost. A methodical rock texture characterization of core samples and cuttings can provide powerful information that can be used reliably and cost-effectively to optimize fracture stimulation designs by placing frac stages based on rock characteristics. This paper presents a new method to quantify rock texture based on automated petrographic analysis that uses advanced microscopy image analysis from scanning electron microscopy (SEM) and optical microscopy. A procedure called "quantitative evaluation of minerals using a scanning electron microscope" (QEMSCAN) and optical microscopy analyses were used to image rock samples prepared from cores and cuttings. Rock texture parameters were extracted automatically using new digital data processing techniques. The information from automated petrographic analysis was used to determine the spatial distribution of all components including mineral composition, framework grains, matrix, cement, grain size and shape, pore size and shape, modes of contact between grains and the nature of porosity. The results showed that while mineral composition of rock is important, texture characterization is far more significant to understand rock behavior than has been reported in the industry. Our results demonstrate the importance of quantitative microscopy and how it can provide an understanding of the key relationship between rock texture and rock behavior.

A new method was produced to characterize rock texture quantitatively from advanced image analysis with the aid of an automated petrographic system.

It is often reported that around 60% of hydraulic fracturing stages are ineffective. If so, it is likely that the design accuracy is limited by the current state of modeling and hydraulic fracture (HF) simulations. Our study presents a new alternative – a full 3-D simulation with geomechanics coupled to fluid flow. With the conventional simulation, it is extremely hard to model opening of weak lamination (Lam) and nearly impossible to generate induced horizontal fractures against the vertical overburden stress. However, horizontal fractures are routinely evident in shale reservoirs as healed fractures observed along the bedding planes. Hence, the need and importance of a true 3-D simulator that could incorporate complex geology and dynamically simulate fracture propagation by accounting for realtime changes in geomechanics and fluid pressures. Case study uses shale reservoirs, which are heavily laminated with complex natural fractures (NFs). Numerical simulations consisted of four separate coupled modules - geomechanics, hydrodynamics, a geomechanical joint model for interfacial resolution, and an adaptive remeshing module. Reservoir stress condition, rock mechanical properties, and injected fluid pressure dictate how fracture elements could open or slide. Critical stress intensity factor was used as a fracture criterion governing the generation of new fractures or propagation of existing fractures and their directions. Simulation was run on a Cray XC-40 HPC system. Typical laminated shale reservoirs anisotropic geomechanical properties obtained from literature were used to estimate a 3-D geomechanical model and NF network. HF geometry was significantly different in the presence of weak bedding, compared to when bedding was strong enough to transmit crack tip stresses across the interface. Significant amounts of fracturing fluid can be diverted into creation of horizontal fractures, even when the pressure was below the vertical stress, once bedding discontinuities are activated. Choices of NF network and Lam thickness significantly affected observed fracture propagation. The value of 3-D modeling was clearly established. This method provides more accurate solutions for stimulation design optimization, e.g., landing points, number of stages, number of clusters, spacing between stages, and stimulated reservoir volume.

A recent geology/mineralogy research group project focusing on carbonate source rock repeatedly observed unique pattern of microfractures. Observations indicated that diagenesis-led mineral distribution predisposes rock to a certain fracture pattern. If this was correct, then next question was whether dolomitization preceded fractures or vice versa. The research effort used advanced microscopy (optical and scanning electron microscopy-SEM) along with high-resolution mineral mapping on many samples to answer these questions. The project established a structural-diagenetic sequence of a dolomitic limestone source rock reservoir and fracturing. Impacts of dolomite influence on fracturing in limestone (mainly composed of calcite minerals) were studied using the quantitative evaluation of minerals obtained from a scanning electron microscope (QEMSCAN) mineral mapping technique. The relationship of other minerals to fracturing such as clay minerals within same rock was also analyzed.

In all observations, dolomitization preceded fractures. This was inferred from the absence of dolomite mineral precipitates within the fracture veins. Other observations noted fractures that cut through the host calcite minerals but were deflected away or around dolomite minerals. In a few instances the deflections created multiple fractures that continued the propagation. Fractures also cut through the clay minerals. This observation implied that the degree of dolomitization and dolomite distribution within the calcite matrix impacted fracture propagation in a carbonate source rock reservoir. A well-dispersed dolomite minerals structure in a limestone source rock reservoir contributed to rock toughness, resisted fracture propagation, and possibly generated multiple fractures, because the dolomite grains acted as stress concentrators. This scenario resulted in a larger surface area created by fractures than the stimulated reservoir volume. The energy required to propagate these fractures was high, compared to fractures that were not affected by dolomite and did not need to change direction. These fractures were expected to remain open to some degree, even after the load was removed, due to the teething created by the need for the fractures to deflect.

These observations have the potential for a better understanding of fracture architecture in relation to mineral distribution within a given rock. This information can provide additional input for consideration when determining fraccability index based on rock properties.

Though ‘Big Data’ has been a much talked topic in recent years, its potential has not been fully utilized to study rocks for the purpose of improving asset development workflow. Our research has been focused on this topic. Upstream research publications combining imaging; elemental analysis and the mineral compositional information to derive a mineral map have recently started. This is very welcome as both SEM (scanning electron) and Optical Microscopy have tremendous latent potential to assist in reservoir characterization including depositional environment and diagenesis and to develop a more accurate reservoir model. In this study we describe new advanced image analysis that combines both SEM and optical microscopy. Results are used to study rock texture and predict rock fracture behavior.

Methods, Procedures, Processes

Carbonate and sandstone rock samples were imaged using QEMSCAN (Quantitative Evaluation of Minerals using Scanning Electron Microscope) and optical microscopy analysis. Rock sections were prepared from cores. New digital data processing techniques were devised to extract the information and compute statistics and eventually automate data extraction.

Results, Observations, Conclusions

The information from image processing such as porosity, grain size, shape, mineral associations, average distance between the neighboring grains, spatial distribution, crack patterns etc. has been used to find correlations between crack propagation and the texture of the rock. Combination of SEM and optical imaging techniques allows one to differentiate between cement and the mineral grains. It is found that the crack pattern is affected by the number of mineral grains per unit area. Higher number of mineral grains per unit area leads to more complex crack pattern which has implications for fraccability. Results show that quantitative microscopy provides a relationship between rock texture and fracture behavior. A new mathematical model is developed to predict the crack length as a function of grain size.

Novelty

While recently XRD/XRF and elemental composition have been more frequently used by Industry, this study focuses on the importance of accurate, comprehensive and quantitative rock texture characterization. Novel image processing techniques and workflows developed by the authors were used to quantify texture. This work also reinforces the case of using complementary microscopy techniques for more accurate and insightful analysis.

Hydraulic fracture stimulation designs are typically made of multiple stages placed along the lateral section of the well using various well completion technologies. Understanding how multiple hydraulic fractures propagate and interact with each other is essential for an effective stimulation design. The number and placement of stages are important factors for optimizing the performance of the laterals. This in turn depends on accuracy in determining fracture interference. We present advanced simulations for accurate placement of well stages. In this paper, we use a 3-D fully coupled geomechanical-fluid flow simulator which incorporates anisotropic geomechanical properties. Densely complex natural fractures and lamination are built into the model based on available core and log information. Multiple fractures are concurrently imployed to simulate real life scenarios. Fluid pressures are incrementally computed such that stress state changes dynamically with time as it happens in real field situation. Our simulations were run on Cray XC 40 HPC system. The results demonstrate that the stress shadow effects can significantly alter hydraulic fracture propagation behavior, which eventually affects the final fracture geometry. The results show that there are large differences in aperture throughout the stimulation which persists to the end of pumping. Furthermore comparison between cases with and without complex natural fractures (discrete fracture network (DFN)) and lamination was conducted with even and uneven spacing configurations. Fracture interference and spacing analysis conducted based on model with perforation frictions shows that while spacing between fractures is important, the largest impact was observed in the presence of lamination and DFN. The large differences in the way the fracture propagates highly depend on the DFN connectivity. Late-stage connection throughout the model implies later disconnection when the pressure drops. Though the computations are time intensive, we believe this is a valuable tool to use in the planning stages for asset development to increase production potential.

This study present a microfacies approach to reservoir-related outcrop analog studies of the exposed discontinuous fringing rhodolith and coral reef complex of Wadi Waqb Member (Miocene Carbonate) of Jabal Kibrit formation in Midyan region, Saudi Arabia. Four facies were recognized as follows: MF-1) Proximal clastic facies comprises of calcallochemic sandstone MF-2) Upper reef front facies characterize by quartz-peloid packstone, and red algal bioclastic boundstone, and MF-3), Lower reef front facies compose of bioturbated rhodophyte-bioclastic grainstone,and MF-4) Fore reef facies comprise of intraclastic wackestone to mudstone. MF-1 represents a mixed carbonate-siliciclastic deposits with very good intergranular porosity preservation in outcrops. However, this porosity does not have any bearing on the Wadi Waqab main reservoir. The preserved primary intergranular and vuggy porosities in MF-2 and MF-3 are considered to be the main components of the Wadi Waqb reservoir. MF-4 possesses no visible porosity in thin section and therefore, does not have any bearing to the main reservoir.